Network energy saving mode enhancements

ABSTRACT

According to an aspect, there is provided an apparatus comprising a data collection configuration for carrying out data collection measurements for training an artificial intelligence or machine learning model used in controlling a mode change in a first radio cell to an energy saving mode.

TECHNICAL FIELD

Various embodiments relate to wireless communications.

BACKGROUND

Energy saving functionality may be utilized to reduce network energyconsumption and energy-related operational expenses. Energy savingdeployments consider capacity booster cells that are deployed on top ofand in addition to coverage cells to enhance capacity for, for example,the universal mobile telecommunications system (UMTS) radio accessnetwork (UT-RAN or E-UTRAN), long term evolution (LTE, the same asE-UTRA), or new radio (NR). Energy efficiency of capacity booster cellscan be optimized by allowing a capacity booster cell being switched offwhen the additional capacity is not needed and re-activated on demand Anaccess node may trigger energy saving actions by switching-off acapacity cell and transferring the related traffic to a coverage cell.

BRIEF DESCRIPTION

According to an aspect, there is provided the subject matter of theindependent claims. Embodiments are defined in the dependent claims. Oneor more examples of implementations are set forth in more detail in theaccompanying drawings and the description below. Other features will beapparent from the description, drawings, and the claims.

LIST OF DRAWINGS

In the following, various example embodiments will be described ingreater detail with reference to the accompanying drawings, in which

FIG. 1 illustrates an example embodiment of a cellular communicationnetwork;

FIG. 2 illustrates a flow chart;

FIG. 3 illustrates a flow chart;

FIG. 4 illustrates a flow chart;

FIG. 5 illustrates a flow chart;

FIG. 6 illustrates a flow chart;

FIG. 7 illustrates a flow chart;

FIG. 8 illustrates a flow chart;

FIG. 9 illustrates a signalling diagram;

FIG. 10 illustrates a signalling diagram;

FIG. 11 illustrates a signalling diagram;

FIG. 12 illustrates an example embodiment of an apparatus;

FIG. 13 illustrates an example embodiment of an apparatus; and

FIG. 14 illustrates an example embodiment of an apparatus.

DETAILED DESCRIPTION OF SOME EMBODIMENTS

The following embodiments are only presented as examples. Although thespecification may refer to “an”, “one”, or “some” embodiment(s) and/orexample(s) in several locations of the text, this does not necessarilymean that each reference is made to the same embodiment(s) orexample(s), or that a particular feature only applies to a singleembodiment and/or example. Single features of different embodimentsand/or examples may also be combined to provide other embodiments and/orexamples.

In the following, different exemplifying embodiments will be describedusing, as an example of an access architecture to which the embodimentsmay be applied, a radio access architecture based on long term evolutionadvanced (LTE Advanced, LTE-A) or new radio (NR, 5G), withoutrestricting the embodiments to such an architecture, however. It isobvious for a person skilled in the art that the embodiments may also beapplied to other kinds of communications networks having suitable meansby adjusting parameters and procedures appropriately. Some examples ofother options for suitable systems are the universal mobiletelecommunications system (UMTS) radio access network (UTRAN orE-UTRAN), long term evolution (LTE, the same as E-UTRA), wireless localarea network (WLAN or WiFi), world-wide interoperability for microwaveaccess (WiMAX), Bluetooth®, personal communications services (PCS),ZigBee®, wideband code division multiple access (WCDMA), systems usingultra-wideband (UWB) technology, sensor networks, mobile ad-hoc networks(MANETs) and Internet Protocol multimedia subsystems (IMS) or anycombination thereof.

FIG. 1 depicts examples of simplified system architectures only showingsome elements and functional entities, all being logical units, whoseimplementation may differ from what is shown. The connections shown inFIG. 1 are logical connections; the actual physical connections may bedifferent. It is apparent to a person skilled in the art that the systemmay comprise also other functions and structures than those shown inFIG. 1 .

The embodiments are not, however, restricted to the system given as anexample but a person skilled in the art may apply the solution to othercommunication systems provided with necessary properties.

The example of FIG. 1 shows a part of an exemplifying radio accessnetwork.

FIG. 1 shows user devices 100 and 102 configured to be in a wirelessconnection on one or more communication channels in a cell with anaccess node (such as (e/g)NodeB) 104 providing the cell. The physicallink from a user device to a (e/g)NodeB is called uplink or reverse linkand the physical link from the (e/g)NodeB to the user device is calleddownlink or forward link. A user device may also communicate directlywith another user device via sidelink (SL) communication. It should beappreciated that (e/g)NodeBs or their functionalities may be implementedby using any node, host, server or access point (AP) etc. entitysuitable for such a usage.

A communications system may comprise more than one (e/g)NodeB, in whichcase the (e/g)NodeBs may also be configured to communicate with oneanother over links, wired or wireless, designed for the purpose. Theselinks may be used for signaling purposes. The (e/g)NodeB is a computingdevice configured to control the radio resources of communication systemit is coupled to. The NodeB may also be referred to as a base station,an access point or any other type of interfacing device including arelay station capable of operating in a wireless environment. The(e/g)NodeB includes or is coupled to transceivers. From the transceiversof the (e/g)NodeB, a connection is provided to an antenna unit thatestablishes bi-directional radio links to user devices. The antenna unitmay comprise a plurality of antennas or antenna elements. The (e/g)NodeBis further connected to core network 110 (CN or next generation coreNGC). Depending on the system, the counterpart on the CN side can be aserving gateway (S-GW, routing and forwarding user data packets), packetdata network gateway (P-GW), for providing connectivity of user devices(UEs) to external packet data networks, or mobile management entity(MME), etc.

The user device (also called UE, user equipment, user terminal, terminaldevice, etc.) illustrates one type of an apparatus to which resources onthe air interface are allocated and assigned, and thus any featuredescribed herein with a user device may be implemented with acorresponding apparatus, such as a relay node.

An example of such a relay node is a layer 3 relay (self-backhaulingrelay) towards the access node. The self-backhauling relay node may alsobe called an integrated access and backhaul (IAB) node. The IAB node maycomprise two logical parts: a mobile termination (MT) part, which takescare of the backhaul link(s) (i.e., link(s) between IAB node and a donornode, also known as a parent node) and a distributed unit (DU) part,which takes care of the access link(s), i.e., child link(s) between theIAB node and user device(s), and/or between the IAB node and other IABnodes (multi-hop scenario).

Another example of such a relay node is a layer 1 relay called arepeater. The repeater may amplify a signal received from an access nodeand forward it to a user device, and/or amplify a signal received fromthe user device and forward it to the access node.

The user device may refer to a portable computing device that includeswireless mobile communication devices operating with or without asubscriber identification module (SIM), including, but not limited to,the following types of devices: a mobile station (mobile phone),smartphone, personal digital assistant (PDA), handset, device using awireless modem (alarm or measurement device, etc.), laptop and/or touchscreen computer, tablet, game console, notebook, and multimedia device.It should be appreciated that a user device may also be a nearlyexclusive uplink only device, of which an example is a camera or videocamera loading images or video clips to a network. A user device mayalso be a device having capability to operate in Internet of Things(IoT) network which is a scenario in which objects are provided with theability to transfer data over a network without requiring human-to-humanor human-to-computer interaction. The user device (or in someembodiments a layer 3 relay node) is configured to perform one or moreof user equipment functionalities. The user device may also be called asubscriber unit, mobile station, remote terminal, access terminal, userterminal or user equipment (UE) just to mention but a few names orapparatuses.

Various techniques described herein may also be applied to acyber-physical system (CPS) (a system of collaborating computationalelements controlling physical entities). CPS may enable theimplementation and exploitation of massive amounts of interconnected ICTdevices (sensors, actuators, processors microcontrollers, etc.) embeddedin physical objects at different locations. Mobile cyber physicalsystems, in which the physical system in question has inherent mobility,are a subcategory of cyber-physical systems. Examples of mobile physicalsystems include mobile robotics and electronics transported by humans oranimals.

It should be understood that, in FIG. 1 , user devices are depicted toinclude 2 antennas only for the sake of clarity. The number of receptionand/or transmission antennas may naturally vary according to a currentimplementation.

Additionally, although the apparatuses have been depicted as singleentities, different units, processors and/or memory units (not all shownin FIG. 1 ) may be implemented.

5G enables using multiple input-multiple output (MIMO) antennas, manymore base stations or nodes than the LTE (a so-called small cellconcept), including macro sites operating in co-operation with smallerstations and employing a variety of radio technologies depending onservice needs, use cases and/or spectrum available. 5G mobilecommunications supports a wide range of use cases and relatedapplications including video streaming, augmented reality, differentways of data sharing and various forms of machine type applications,including vehicular safety, different sensors and real-time control. 5Gis expected to have multiple radio interfaces, namely below 6 GHz,cmWave and mmWave, and also being integrable with existing legacy radioaccess technologies, such as the LTE. Integration with the LTE may beimplemented, at least in the early phase, as a system, where macrocoverage is provided by the LTE and 5G radio interface access comes fromsmall cells by aggregation to the LTE. In other words, 5G is planned tosupport both inter-RAT operability (such as LTE-5G) and inter-RIoperability (inter-radio interface operability, such as below 6GHz—cmWave, below 6 GHz—cmWave—mmWave). One of the concepts consideredto be used in 5G networks is network slicing in which multipleindependent and dedicated virtual sub-networks (network instances) maybe created within the same infrastructure to run services that havedifferent requirements on latency, reliability, throughput, andmobility.

The current architecture in LTE networks is fully distributed in theradio and fully centralized in the core network. The low latencyapplications and services in 5G require to bring the content close tothe radio which leads to local break out and multi-access edge computing(MEC). 5G enables analytics and knowledge generation to occur at thesource of the data. This approach requires leveraging resources that maynot be continuously connected to a network such as laptops, smartphones,tablets, and sensors. MEC provides a distributed computing environmentfor application and service hosting. It also has the ability to storeand process content in close proximity to cellular subscribers forfaster response time. Edge computing covers a wide range of technologiessuch as wireless sensor networks, mobile data acquisition, mobilesignature analysis, cooperative distributed peer-to-peer ad hocnetworking and processing also classifiable as local cloud/fog computingand grid/mesh computing, dew computing, mobile edge computing, cloudlet,distributed data storage and retrieval, autonomic self-healing networks,remote cloud services, augmented and virtual reality, data caching,Internet of Things (massive connectivity and/or latency critical),critical communications (autonomous vehicles, traffic safety, real-timeanalytics, time-critical control, healthcare applications).

The communication system is also able to communicate with othernetworks, such as a public switched telephone network or the Internet112, or utilise services provided by them. The communication network mayalso be able to support the usage of cloud services, for example atleast part of core network operations may be carried out as a cloudservice (this is depicted in FIG. 1 by “cloud” 114). The communicationsystem may also comprise a central control entity, or a like, providingfacilities for networks of different operators to cooperate for examplein spectrum sharing.

Edge cloud may be brought into radio access network (RAN) by utilizingnetwork function virtualization (NVF) and software defined networking(SDN). Using edge cloud may mean access node operations to be carriedout, at least partly, in a server, host or node operationally coupled toa remote radio head or base station comprising radio parts. It is alsopossible that node operations will be distributed among a plurality ofservers, nodes, or hosts. Application of cloudRAN architecture enablesRAN real time functions being carried out at the RAN side (in adistributed unit, DU 104) and non-real time functions being carried outin a centralized manner (in a centralized unit, CU 108).

It should also be understood that the distribution of labour betweencore network operations and base station operations may differ from thatof the LTE or even be non-existent. Some other technology advancementsprobably to be used are Big Data and all-IP, which may change the waynetworks are being constructed and managed. 5G (or new radio, NR)networks are being designed to support multiple hierarchies, where MECservers can be placed between the core and the base station or nodeB(gNB). It should be appreciated that MEC can be applied in 4G networksas well.

5G may also utilize satellite communication to enhance or complement thecoverage of 5G service, for example by providing backhauling. Possibleuse cases are providing service continuity for machine-to-machine (M2M)or Internet of Things (IoT) devices or for passengers on board ofvehicles, or ensuring service availability for critical communications,and future railway/maritime/aeronautical communications. Satellitecommunication may utilise geostationary earth orbit (GEO) satellitesystems, but also low earth orbit (LEO) satellite systems, in particularmega-constellations (systems in which hundreds of (nano)satellites aredeployed). Each satellite 106 in the mega-constellation may coverseveral satellite-enabled network entities that create on-ground cells.The on-ground cells may be created through an on-ground relay node 104or by a gNB located on-ground or in a satellite.

It is obvious for a person skilled in the art that the depicted systemis only an example of a part of a radio access system and in practice,the system may comprise a plurality of (e/g)NodeBs, the user device mayhave an access to a plurality of radio cells and the system may comprisealso other apparatuses, such as physical layer relay nodes or othernetwork elements, etc. At least one of the (e/g)NodeBs may be aHome(e/g)nodeB.

Furthermore, the access node may also be split into: a radio unit (RU)comprising a radio transceiver (TRX), i.e., a transmitter (Tx) and areceiver (Rx); one or more distributed units (DUs) that may be used forthe so-called Layer 1 (L1) processing and real-time Layer 2 (L2)processing; and a central unit (CU) (also known as a centralized unit)that may be used for non-real-time L2 and Layer 3 (L3) processing. TheCU may be connected to the one or more DUs for example by using an F1interface. Such a split may enable the centralization of CUs relative tothe cell sites and DUs, whereas DUs may be more distributed and may evenremain at cell sites. The CU and DU together may also be referred to asbaseband or a baseband unit (BBU). The CU and DU may also be comprisedin a radio access point (RAP).

The CU may be defined as a logical node hosting higher layer protocols,such as radio resource control (RRC), service data adaptation protocol(SDAP), and/or packet data convergence protocol (PDCP), of the accessnode. The DU may be defined as a logical node hosting radio link control(RLC), medium access control (MAC), and/or physical (PHY) layers of theaccess node. The CU may further comprise a user plane (CU-UP), which maybe defined as a logical node hosting the user plane part of the PDCPprotocol and the SDAP protocol of the CU for the access node.

Cloud computing platforms may also be used to run the CU and/or DU. TheCU may run in a cloud computing platform, which may be referred to as avirtualized CU (vCU). In addition to the vCU, there may also be avirtualized DU (vDU) running in a cloud computing platform. Furthermore,there may also be a combination, where the DU may use so-called baremetal solutions, or example application-specific integrated circuit(ASIC) or customer-specific standard product (CSSP) system-on-a-chip(SoC) solutions. It should also be understood that the distribution oflabour between the above-mentioned base station units, or different corenetwork operations and base station operations, may differ.

Additionally, in a geographical area of a radio communication system aplurality of different kinds of radio cells as well as a plurality ofradio cells may be provided. Radio cells may be macro cells (or umbrellacells) which are large cells, usually having a diameter of up to tens ofkilometers, or smaller cells such as micro-, femto-, or picocells. The(e/g)NodeBs of FIG. 1 may provide any kind of these cells. A cellularradio system may be implemented as a multilayer network includingseveral kinds of cells. In multilayer networks, one access node mayprovide one kind of a cell or cells, and thus a plurality of (e/g)NodeBsare required to provide such a network structure.

For fulfilling the need for improving the deployment and performance ofcommunication systems, the concept of “plug-and-play” (e/g)NodeBs hasbeen introduced. A network which is able to use “plug-and-play”(e/g)Node Bs, may include, in addition to Home (e/g)NodeBs(H(e/g)nodeBs), a home node B gateway, or HNB-GW (not shown in FIG. 1 ).A HNB Gateway (HNB-GW), which may be installed within an operator'snetwork, may aggregate traffic from a large number of HNBs back to acore network.

6G networks are expected to adopt flexible decentralized and/ordistributed computing systems and architecture and ubiquitous computing,with local spectrum licensing, spectrum sharing, infrastructure sharing,and intelligent automated management underpinned by mobile edgecomputing, artificial intelligence, short-packet communication andblockchain technologies. Key features of 6G will include intelligentconnected management and control functions, programmability, integratedsensing and communication, reduction of energy footprint, trustworthyinfrastructure, scalability, and affordability. In addition to these, 6Gis also targeting new use cases covering the integration of localizationand sensing capabilities into system definition to unifying userexperience across physical and digital worlds.

5G and 6G networks, and beyond, are expected to use artificialintelligence or machine learning in controlling energy savingfunctionalities. Below different examples of how to at least obtain datafor training and re-training of the artificial intelligence or machinelearning model are discussed, using data related to a first radio cellas a non-limiting example. The first radio cell may be, for example, acapacity booster cell that may be deployed on top of a coverage cell toenhance capacity. The capacity booster cell may be allowed to beoptimized by being switched off when capacity is not needed andre-activated on demand The first radio cell may also be, for example, acoverage cell that may be switched off. The artificial intelligence ormachine learning model may be a different model for different accessnodes, or it may be shared by a plurality of access nodes, or it may onemodel shared by the radio access network.

FIG. 2 illustrates a flow chart according to an example functionality ofan apparatus configured to receive measurement and reportingconfigurations and to apply them, for example to collect data fortraining an artificial intelligence or machine learning (AI/ML) modelthat may be used in controlling the energy saving functionalities.

Referring to FIG. 2 , a configuration for neighbour cell measurements isreceived in block 201 from an access node. The configuration forneighbour cell measurements may also have been received earlier as partof a normal procedure. The apparatus may receive the configuration forneighbour cell measurements in system information (SI), for example,during cell selection or re-selection processes, during returning fromout of coverage, when receiving an indication that SI is modified, whenreceiving a public warning system (PWS) modification, when entering thecommunication network, or when reconfiguration with synchronization isfinished. A message comprising information associated with a mode changein a first radio cell to an energy saving mode is received in block 202from the access node. The change of mode may further be associated to anenergy saving AI/ML decision that predicts that the first radio cell isexpected to soon enter energy saving mode. The message may be, forexample, a short message transmitted on physical downlink controlchannel (PDCCH) using paging radio network temporary identifier (P-RNTI)with or without associated paging message using short message field.Spare bits of the short message may be used for this. Data collectionconfiguration information for carrying out data collection measurementsfor training an artificial intelligence or machine learning model isreceived in block 203 in relation to the message. The artificialintelligence or machine learning model in training may be an artificialintelligence or machine learning model deciding the mode change in block(202), e.g., predicting that the capacity booster cell will be switchedoff in a future time. The apparatus may receive the information in asystem information block SIBx, dedicated to conveying data collectionconfiguration information, or in a modified system information block SIB1. Further information may be read by the apparatus, for example, insystem information blocks SIB3/4/5. Depending on an implementation, theinformation may be read by the apparatus at next system informationcycle, or the apparatus may request the information, for example, byusing an on demand system information request, and then read theinformation in a response to the request. The data collectionconfiguration information, i.e., information on a data collectionconfiguration, may indicate a preset configuration or comprise theconfiguration or a part of the configuration. The preset data collectionconfiguration may be a radio resource control (RRC) measurementconfiguration that will be applied in response to the apparatusreceiving information that the energy saving mode will be activated andwhich may have been received earlier as part of the normal procedure.The configuration may also comprise a set of prioritized frequenciesand/or cells that the apparatus should prioritize with the datacollection measurements. The information may also comprise a set ofblacklisted frequencies and/or cells the apparatus should avoid with thedata collection measurements. Information on the blacklisted cellsand/or frequencies may be received, for example, in SIB3:intraFreqBlackCellList, SIB4: interFreqBlackCellList, or Sib5:eutra-BlackCellList. The data collection measurements are carried outand the related results transmitted in block 204 to the access node. Thedata collection measurements are carried out in block 204 according tothe data collection configuration at least until a handover procedureassociated with the mode change is started, or until a new command tostop the data collection is received from the access node. In theillustrated example, the data collection measurements are carried outuntil a handover command is received. The data collection measurementsmay be radio resource control measurements, for example, referencesignal received power (RSRP) or reference signal received quality(RSRQ). The neighbour cell measurements are carried out and the relatedresults transmitted in block 205 to the access node for the handoverprocedure. The measurements and reporting in blocks 204 and 205 areperformed in the illustrated example until in block 206 it is detectedthat a handover command for the handover procedure associated with themode change is received. When the handover command is received (block206: yes), the process continues in block 207 with a handover to asecond cell. The second cell may be a coverage cell or another capacitybooster cell that is not switched off. The data collection measurementsand the neighbour cell measurements may also be carried out in adifferent order, and the frequency of the measurements may be different,for example data collection measurements may be carried out every Xseconds, and neighbour cell measurements every Z seconds, X beingsmaller than Z.

FIG. 3 illustrates a flow chart according to an example functionality ofan apparatus in an implementation in which only a subset of apparatusesis to be configured to receive measurement and reporting configurationsand to apply them, for example to collect data for training anartificial intelligence or machine learning model that may be used incontrolling the energy saving functionality.

Referring to FIG. 3 , a configuration for neighbour cell measurements isreceived in block 301 from an access node. A message comprisinginformation associated with a mode change in a first radio cell to anenergy saving mode is received in block 302 from the access node. Datacollection configuration information for carrying out data collectionmeasurements for training an artificial intelligence or machine learningmodel and an associated first condition are received in block 303 inrelation to the message. The first condition may comprise a serviceidentifier, a slice identifier, a quality of service identifier, forexample 5QI, a public land mobile network (PLMN) identifier, anidentifier identifying a non-public network (NPN), e.g., a combinationof a PLMN identifier and a network identifier (NID) that identifies astandalone NPN (S-NPN), or a CAG-ID identifying a public networkintegrated NPN (PNI-NPN). The first condition may further bearea-dependent, comprising a cell or a list of cells, UE state-dependentand depending on the UE remaining battery life or UE type, to give someexamples. For example, the first condition may indicate a bearer with5QI, and the apparatus has such a bearer active. The first condition maybe determined as met if at least one of the identifiers comprised in thefirst condition corresponds to an active bearer, or it may also bedetermined as met when a plurality of identifiers comprised in the firstcondition corresponds to active bearers. The identifiers comprised inthe first condition may also have a priority order in which theapparatus checks if they correspond to an active bearer. The firstcondition may also comprise a specific trace identifier to trigger asubset of apparatuses to report measurements based on, for example,cell-based criteria. The first condition may also comprise one or moreidentifiers of apparatuses to be configured, which may have beendetermined using a randomizing factor to avoid synchronizing a largenumber of apparatuses to report at the same time. The first conditionmay also be based on an energy saving event, which may be determined,for example, by comparing the serving cell or frequency to the bestneighbour cell/frequency according to a threshold. The threshold may bedefined different for model training phase and model inference phase, orit may be defined the same. The process checks in block 304 if the firstcondition is met. If the first condition is met (block 304: yes),further information may be read by the apparatus, for example, in systeminformation blocks SIB3/4/5 and the process continues in block 305 toblock 204 in FIG. 2 . If the first condition is not met (block 305: no),the data collection configuration is ignored and data collection is nottriggered in block 306. Even though not illustrated in FIG. 3 , theapparatus carries out neighbour cell measurements according to thenormal procedure and transmits related results to the access node forthe handover procedure. The process may also continue to again check inblock 304 if the first condition is met.

FIG. 4 illustrates a flow chart according to an example functionality ofan apparatus configured to collect data for training an artificialintelligence or machine learning model in an implementation includingpro-active handovers. The pro-active handover may be triggered even whenthe first cell is still better than the second cell, as opposed to theclassical “reactive” handover. The example functionality may be combinedwith any of the functionalities described with FIG. 2 or 3 .

Referring to FIG. 4 , a configuration for neighbour cell measurements isreceived in block 401 from an access node. A message comprisinginformation associated with a mode change in a first radio cell to anenergy saving mode is received in block 402 from the access node. Datacollection configuration information for carrying out data collectionmeasurements for training an artificial intelligence or machine learningmodel and associated second condition for starting a handover procedureare received in block 403 in relation to the message. The secondcondition is a condition for the pro-active handover. The secondcondition may be at least one of, for example, that a difference betweenthe first radio cell and a highest priority neighbour cell becomessmaller than a threshold, or a difference between a serving frequencyand a highest priority neighbour frequency becomes smaller than athreshold. The highest priority neighbour cell/frequency may be acoverage cell/frequency that has a low priority for energy saving due tothat, for example, it may be energy-efficient (in terms of a bits/joulemetric) compared to other cells/frequencies, or it may have a lowenergy-consumption. The second condition may also be at least one of,for example, a difference between the first radio cell and a bestneighbour cell that is not one of blacklisted cells becomes smaller thana threshold, or a difference between the serving frequency and a bestneighbour frequency that is not one of blacklisted frequencies becomessmaller than a threshold. A blacklisted cell/frequency may be acell/frequency that has been indicated to be switched off, it may have ahigh energy-consumption (in terms of consumed joules), or it may have alow energy-efficiency compared to other frequencies/cells. The secondcondition may also comprise a number of times the measurements are to becarried out before starting a pro-active handover procedure, forexample, indicating the apparatus to carry out the measurements once andthen start the handover procedure. The second condition may alsocomprise a pre-determined time period after receiving the secondcondition after which the pro-active handover procedure is to bestarted. The data collection measurements and neighbour cellmeasurements are carried out and the related results transmitted inblock 404 to the access node, as described with FIG. 2 above, until itis detected in block 405 that the second condition is met. When thesecond condition is met (block 405: yes), the pro-active handoverprocedure is started in block 406. The process checks in block 407 if ahandover command is received. The handover command is a handover commandfor the pro-active handover associated with the mode change. If thehandover command is received (block 407: yes), the process continues inblock 408 by carrying out a handover to a second radio cell. If nohandover command is received (block 407: no), the measurements arecarried out and the related results transmitted in block 409 to theaccess node, as described above, until the handover command is received.

FIG. 5 illustrates a flow chart according to an example functionality ofan apparatus configured to collect data for training an artificialintelligence or machine learning model used in controlling the energysaving functionalities in an implementation including associating datacollection measurements related results with additional information tohelp distinguishing the results from other measurements related resultsto obtain data for the training. The example functionality may becombined with any of the functionalities described with FIGS. 2 to 4 .

Referring to FIG. 5 , a configuration for neighbour cell measurements isreceived in block 501 from an access node. A message comprisinginformation associated with a mode change in a first radio cell to anenergy saving mode is received in block 502 from the access node. Datacollection configuration information for carrying out data collectionmeasurements for training an artificial intelligence or machine learningmodel is received in block 503 in relation to the message. The datacollection measurements are carried out in block 504. The datacollection measurements related results are associated in block 505 withadditional information indicating that the results are data collectedfor training the artificial intelligence or machine learning model. Theadditional information may also comprise an identifier that may be usedto identify the apparatus that has provided the measurements, forexample, a trace identifier that has been used to collect measurements.Thus, collecting measurements may be limited to a specific traceidentifier that may trigger a subset of apparatuses to reportmeasurements based on, for example, cell-based criteria. The results arethen transmitted in block 506 to the access node. The data collectionmeasurements are carried out in block 504 according to the datacollection configuration at least until a handover procedure associatedwith the mode change is started. The neighbour cell measurements arecarried out and the related results transmitted in block 507 to theaccess node for the handover procedure. The measurements and reportingin blocks 504 and 507 are performed in the illustrated example until itis detected in block 508 that a handover command for the handoverprocedure associated with the mode change is received. When the handovercommand is received (block 508: yes), the process continues in block 509with a handover to a second cell.

FIG. 6 illustrates a flow chart according to an example functionality ofan apparatus configured to collect data for training an artificialintelligence or machine learning model used in controlling the energysaving functionalities in an implementation including continuingmeasurements and reporting after a pro-active handover to obtaininformation from the whole time before a cell is switched off. Theexample functionality may be combined with any of the functionalitiesdescribed with FIGS. 2 to 5 .

Referring to FIG. 6 , a configuration for neighbour cell measurements isreceived in block 601 from an access node. A message comprisinginformation associated with a mode change in a first radio cell to anenergy saving mode is received in block 602 from the access node. Datacollection configuration information for carrying out data collectionmeasurements for training an artificial intelligence or machine learningmodel and an associated instruction to continue carrying out the datacollection measurements and transmitting after a handover procedure arereceived in block 603 in relation to the message. The data collectionmeasurements and the neighbour cell measurements are carried out and therelated results transmitted in block 604 to the access node. Themeasurements and reporting in block 604 are performed in the illustratedexample until it is detected in block 605 that a handover command forthe handover procedure associated with the mode change is received. Whenthe handover command is received (block 605: yes), the process continuesin block 606 with a handover to a second cell. The handover command maycomprise instructions on whether to continue the measurements andreporting after handover. After the handover to the second cell, thedata collection measurements are carried out and the related resultstransmitted in block 607 to the second radio cell. The configuration maycomprise, for example, a time period for how long the measurements andreporting will be continued. The apparatus may also be instructed by thesecond radio cell whether to continue the measurements and reporting,and/or when to terminate the measurements and reporting.

FIG. 7 illustrates a flow chart according to an example functionality ofan apparatus configured to configure apparatuses, for example asdescribed above with FIGS. 2 to 6 , to collect data for training anartificial intelligence or machine learning model used in controllingthe energy saving functionalities relating to the apparatus.

Referring to FIG. 7 , a configuration for neighbour cell measurements isdetermined and transmitted in block 701 at least to a plurality ofapparatuses in a first radio cell. In the illustrated example, when amode change in the first radio cell to an energy saving mode isinitiated, a data collection configuration for carrying out datacollection measurements for a mode change in the first radio cell to anenergy saving mode is determined in block 702. The data collectionmeasurements are carried out for obtaining training data for training orretraining the artificial intelligence or machine learning model and/orfor obtaining input data (including inference data) to said artificialintelligence or machine learning model. The mode change may be performedby a power ramp-down method, wherein step size and step duration may bedetermined using load information or predicted load informationavailable to the access node. The mode change may be also performedafter a predetermined time period after information associated with themode change has been transmitted. When the mode change in the firstradio cell to the energy saving mode is initiated, a message comprisingthe information associated with the mode change and, in relation to themessage, data collection configuration information are transmitted inblock 703 to the plurality of apparatuses. The data collectionconfiguration information, i.e., information on a data collectionconfiguration, may indicate a preset configuration or comprise theconfiguration or a part of the configuration. Results related to thedata collection measurements and the neighbour cell measurements for ahandover procedure associated with the mode change are received in block704 from at least one of the plurality of apparatuses. A handovercommand to carry out a handover to a second radio cell is transmitted inblock 705 to the at least one apparatus.

FIG. 8 illustrates a flow chart according to an example functionality ofan apparatus configured to configure a subset of apparatuses to collectdata for training an artificial intelligence or machine learning modelused in controlling the energy saving functionalities.

Referring to FIG. 8 , a configuration for neighbour cell measurements isdetermined and transmitted in block 801 at least to a plurality ofapparatuses in a first radio cell. A data collection configuration forcarrying out data collection measurements for a mode change in the firstradio cell to an energy saving mode is determined in block 802. The datacollection measurements are carried out for training an artificialintelligence or machine learning model used in controlling the modechange in the first radio cell. When the mode change in the first radiocell to the energy saving mode is initiated, a message comprisinginformation associated with the mode change and, in relation to themessage, data collection configuration information are transmitted inblock 803 to the plurality of apparatuses. Counters for determining dataare initialized in block 804. Results related to the measurements arereceived in block 805 from at least one of the plurality of apparatuses.A handover command to carry out a handover to a second radio cell istransmitted in block 806 to the subset of apparatuses. Data for trainingthe artificial intelligence or machine learning model is determined inblock 807 from the counters and the results received. The data maycomprise at least one of: a number of radio link failures that occurafter the mode change in the first radio cell to the energy saving modeis initiated, a number of connection re-establishments that occur afterthe mode change in the first radio cell to the energy saving mode isinitiated, a number of handover preparation failures that occur afterthe mode change in the first radio cell to the energy saving mode isinitiated, a handover success rate after the mode change in the firstradio cell to the energy saving mode is initiated, a handover failurerate after the mode change in the first radio cell to the energy savingmode is initiated, a number of early handovers that occur after the modechange in the first radio cell to the energy saving mode is initiated,and/or a number of late handovers that occur after the mode change inthe first radio cell to the energy saving mode is initiated.

FIG. 9 and FIG. 10 illustrate signalling diagrams according to examplesof information exchange in a communication network configured to collectdata for training an artificial intelligence or machine learning modelused in controlling the energy saving functionalities, and to initiate aprioritized handover mechanism to a subset of apparatuses when a modechange to an energy saving mode in a first radio cell is initiated. Thetrained artificial intelligence or machine learning model may be used indetermining when the mode change is initiated. The pro-active handovermechanism may also reduce the number of undesirable radio link failure(RLF) events and shorten the time needed for cell shutdown. For the sakeof clarity, messages associated with neighbour cell measurementconfiguration are not illustrated in FIG. 9 and FIG. 10 . In FIG. 9 andFIG. 10 , term “AN1” is used for a currently serving access node, i.e.,an access node providing the first radio cell. Term “AN2” is used for anaccess node providing a target cell in the handover. The access nodesmay be, for example, gNB(s) or a distributed access node, comprising forexample a centralized unit (CU) and a distributed unit (DU) enabling RANreal time functions being carried out at the RAN side (in the DU) andnon-real time functions being carried out in a centralized manner (inthe CU). Term “UE1” is used for an apparatus, or a subset of apparatusesreceiving configuration information for data collection and being handedover through a pro-active handover mechanism. Term “UE2” is used foranother one or more apparatuses configured to be handed over through alegacy reactive handover mechanism.

Referring to FIG. 9 , the AN1 transmits (message 9-1) to the AN2 arequest to forward results related to data collection measurements tothe AN1. Upon receiving said request, the AN2 acknowledges it bytransmitting message 9-2. The request (message 9-1) and theacknowledgement (message 9-2) AN2 may also be transmitted later in theprocess, for example after block 9-5 or as part of the handover (block9-8). A first condition for configuring a subset of apparatuses with adata collection configuration and a second condition for the pro-activehandover are determined in block 9-3 by the AN1. The first condition maycomprise a service identifier, a slice identifier, a quality of serviceidentifier, for example 5QI, a public land mobile network (PLMN)identifier, an identifier identifying a non-public network (NPN), e.g.,a combination of PLMN identifier and network identifier (NID) thatidentifies a standalone NPN (S-NPN), or a CAG-ID identifying a publicnetwork integrated NPN (PNI-NPN). The first condition may further bearea-dependent, comprising a cell or a list of cells, UE state-dependentand depending on the UE remaining battery life or UE type, to give someexamples. The first condition may be determined as met if at least oneof the identifiers comprised in the first condition corresponds to anactive bearer, or it may also be determined as met when a plurality ofidentifiers comprised in the first condition corresponds to activebearers. The first condition may also comprise a specific traceidentifier to trigger a subset of apparatuses to report measurementsbased on, for example, cell-based criteria. The first condition may alsocomprise one or more identifiers of apparatuses to be configured, whichmay be determined using a randomizing factor to avoid synchronizing alarge number of apparatuses to report at the same time. The firstcondition may also be based on an energy saving event, which may bedetermined, for example, by comparing the serving cell or frequency tothe best neighbour cell/frequency according to a threshold. Thethreshold may be defined differently for model training phase and modelinference phase, or it may be defined to be the same. The secondcondition may be at least one of, for example, that a difference betweenthe first radio cell and a highest priority neighbour cell becomessmaller than a threshold, or a difference between a serving frequencyand a highest priority neighbour frequency becomes smaller than athreshold. The highest priority neighbour cell/frequency may be acoverage cell/frequency that has a low priority for energy saving due tothat, for example, it may be energy-efficient (in terms of a bits/joulemetric) compared to other cells/frequencies, or it may have a lowenergy-consumption. The second condition may also be at least one of,for example, a difference between the first radio cell and a bestneighbour cell that is not one of blacklisted cells becomes smaller thana threshold, or a difference between the serving frequency a bestneighbour frequency that is not one of blacklisted frequencies becomessmaller than a threshold. A blacklisted cell/frequency may be acell/frequency that has been indicated to be switched off, it may have ahigh energy-consumption (in terms of consumed joules), or it may have alow energy-efficiency compared to other frequencies/cells. The secondcondition may also comprise a number of times the measurements are to becarried out before starting the pro-active handover procedure, forexample, indicating the apparatus to carry out the measurements once andthen start the handover procedure. The second condition may alsocomprise a pre-determined time period after receiving the one or moreconditions after which the pro-active handover procedure is to bestarted. Further, the AN1 transmits (messages 9-4 a and 9-4 b) to theUE1 and the UE2 a message comprising information associated with themode change and, in relation to the message, data collectionconfiguration information (messages 9-4 a and 9-4 b) comprising thefirst condition and the second condition. Upon receiving messages 9-4 aand 9-4 b, it is checked in block 9-5 by the UE1 and the UE2 if thefirst condition is met. In the illustrated example, the first conditionis met by the UE1, and the UE1 transmits (message 9-6) results relatedto the data collection measurements to the AN1. In the illustratedexample, the first condition is not met by the UE2, and the UE2 ignoresmessage 9-4 b. The UE2 may also respond to AN1 that the absence ofmeasurements is due to the first condition not being met. It is checkedin block 9-7 by the UE1 if the second condition is met. In response tothe second condition being met, the UE1 is handed over in block 9-8 toAN2 through the pro-active handover mechanism, for example, by the UE1transmitting a request for handover, and in response to the requestreceiving a handover command The actual handover procedure is similar tothe procedure in the reactive handover, the difference being that thepro-active handover is triggered earlier. The UE1 transmits (message9-9) results related to the data collection measurements to AN2 and theAN2 forwards (message 9-10) the results to the ANI. The AN1 checks inblock 9-11 if the UE1, or all of the subset of UE1, is/are handed overand when it is/they are, then triggers in block 9-12 a graceful shutdownof the first radio cell. Then the UE2, or the subset of UE2s is/arehanded over in block 9-13 to the AN2 through the legacy reactivehandover mechanism. The cell switch-off may be carried out, for example,by a power ramp-down with steps whose duration and number may beprovided in system information, until a complete cell switch-off isachieved. The trained artificial intelligence or machine learning modelmay be used in determining the duration and number of power ramp-downsteps to obtain a reduced number of radio link failure events. Inresponse to the first cell being switched-off, the AN1 transmits(message 9-14) to the AN2 information that the first cell isswitched-off. In response to receiving message 9-14, the AN2 transmits(message 9-15) to the UE1 instructions on how to terminate carrying outthe data collection measurements and transmitting the related results.Enabling pro-active handover of the UE1, which may be the most importantsubset of apparatuses, before shutdown may reduce the number ofundesirable radio link failure (RLF) events and shorten the duration oftime before a desired cell switch-off. The results related to the datacollection measurements may be mapped to current energy saving policy,and they may help updating the current energy saving policy with respectto how successful the handover was. In another example without the firstcondition, there is no UE2. Then block 9-11 may be replaced with, forexample, a predefined time after sending message 9-4 a, after which thesubset of UE1s that have not yet been handed over in block 9-8 throughthe pro-active handover mechanism will be handed over in block 9-13through the legacy reactive handover mechanism.

Referring to FIG. 10 , a first condition for configuring a subset ofapparatuses with a data collection configuration and a second conditionfor the pro-active handover are determined in block 10-1 by the AN1 asexplained in more detail above with FIG. 9 . The AN1 transmits (messages10-2 a and 10-2 b) to the UE1 and the UE2 a message comprisinginformation associated with the mode change and, in relation to themessage, data collection configuration information (messages 10-2 a and10-2 b) comprising the first condition. Upon receiving messages 10-2 aand 10-2 b, it is checked in block 10-3 by the UE1 and the UE2 if thefirst condition is met. In the illustrated example, the first conditionis met by the UE1, and the UE1 transmits (message 10-4) results relatedto the data collection measurements to the AN1. In the illustratedexample, the first condition is not met by the UE2, and the UE2 mayignore message 10-2 b (as an alternative the UE2 may respond that theabsence of measurements is due to the first condition not being met). Itis checked in block 10-5 by the UE1 if the second condition is met. Inresponse to the second condition being met, the UE1 is handed over inblock 10-6 to AN2 through the pro-active handover mechanism, forexample, by the UE1 transmitting a request for handover, and in responseto the request receiving a handover command The AN1 checks in block 10-7if the UE1, or all of the subset of UE1, is/are handed over, and when itis/they are, then switches off in block 10-8 the first radio cell. Thenthe UE2, or subset of UE2s is/are handed over in block 10-9 to the AN2through the legacy reactive handover mechanism. Enabling pro-activehandover of the UE1, which may be the most important apparatuses, beforeshutdown may reduce the number of undesirable radio link failure (RLF)events. In another example without the first condition, there is no UE2.Then block 10-7 may be replaced with, for example, a predefined timeafter sending message 10-2 a, after which the subset of UE1s that havenot yet been handed over in block 10-6 through the pro-active handovermechanism will be handed over in block 10-9 through the legacy reactivehandover mechanism.

FIG. 11 illustrates a signalling diagram according to an example ofinformation exchange in a communication network configured to train anartificial intelligence or machine learning model and use the trainedmodel in controlling the energy saving functionalities. The illustratedentities are logical entities that may locate in one node, in which casethe information exchange may be internal information exchange, or thelogical entities may locate in different nodes, or two of them maylocate in one node and one in a further node. Further, the communicationnetwork may comprise a plurality of any of the illustrated logicalentities. The term “Access node” is used for an access node collectingdata for training the artificial intelligence or machine learning model.Term “Model training” is used for the process of training the artificialintelligence or machine learning model with the data collected. Thestructure of the artificial intelligence of machine learning model isnot significant regarding collecting data for training the model and itis therefore not described in more detail here. Term “Model inference”is used for the process of using the trained artificial intelligence ormachine learning model in controlling the energy saving functionalities.It should be appreciated that the signalling illustrated may be internalsignalling within an access node, or an access node may be configured toperform training the artificial intelligence or machine learning model.

Referring to FIG. 11 , the Access node 11-1 transmits (message 11-2)collected input data to Model training 11-3. Input data for theartificial intelligence or machine learning model may comprise, forexample, information on coverage cells and capacity cells, preventivemaintenance counters on radio link failure events, preventivemaintenance counters on re-establishment events, preventive maintenancecounters on handover preparation failures to neighbour cells during cellshutdown period triggered by the mode change, preventive maintenancecounters on handover success and/or failure rates to the neighbour cellsduring cell shutdown period, preventive maintenance counters on mobilityrobustness optimization (MRO), energy efficiency and/or energyconsumption of the neighbour cells, and/or resource status of theneighbour cells. Parameters obtained by training the artificialintelligence or machine learning model are then transmitted (message11-5) to Model inference 11-4. The Access node 11-1 transmits (message11-6) collected input data to Model inference and receives (message11-7) artificial intelligence or machine learning model output forcontrolling the energy saving functionalities. Inference data, that is,the output of the artificial intelligence or machine learning modelinference, may comprise cell shutdown policy parameters, for example,start time, duration, and/or step size for the power-ramp down, resourcestatus of the neighbour cells, and/or evaluation criteria that maymaximize the handover success rate. The output of the trained artificialintelligence or machine learning model may be used to update cellshutdown policy parameters. Performance of the trained artificialintelligence or machine learning model may be monitored by observing areduction of radio link failure events and an increase of handoversuccess key performance indicators. Model performance feedback may betransmitted (message 11-8) from Model inference to Model training forfurther training of the artificial intelligence or machine learningmodel and updated artificial intelligence or machine learning modelparameters may be transmitted (message 11-5) from Model training toModel inference.

As can be seen from the above examples, the additional configuration formeasurements may enable, for example, obtaining training data from UEs,triggering handover with conditions suitable for entering an energysaving mode, and optimizing energy saving cell shutdown policyparameters according to the deployment area (for example urban or rural)to obtain dynamic policies used for cell switch-off decision instead ofstatic policies.

The blocks, related functions, and information exchanges (messages)described above by means of FIGS. 2 to 11 are in no absolutechronological order, and some of them may be performed simultaneously orin an order differing from the given one. Other functions can also beexecuted between them or within them, and other information may be sent,and/or other rules applied. Some of the blocks or part of the blocks orone or more pieces of information can also be left out or replaced by acorresponding block or part of the block or one or more pieces ofinformation.

FIG. 12 illustrates an example embodiment of an apparatus 1201, whichmay be an apparatus such as, or comprised in, a user device. Theapparatus 1201 may correspond to any of the user devices 100, 102 ofFIG. 1 . The apparatus may also be called a subscriber unit, mobilestation, remote terminal, access terminal, user terminal, terminaldevice, user equipment (UE), vehicle, or any electric device.

The apparatus 1201 may comprise one or more communication controlcircuitry 1220, such as at least one processor, and at least one memory1230, including one or more algorithms 1231, such as a computer programcode (software) wherein the at least one memory and the computer programcode (software) are configured, with the at least one processor, tocause the apparatus to carry out any one of the example functionalitiesof the apparatus described above. Said at least one memory 1230 may alsocomprise at least one database 1232.

Referring to FIG. 12 , the one or more communication control circuitry1220 of the apparatus 1201 comprise at least measurement circuitry 1221which is configured to perform data collection measurements according toembodiments. To this end, the measurement circuitry 1221 of theapparatus 1201 is configured to carry out at least some of thefunctionalities of the apparatus described above, e.g., by means ofFIGS. 2 to 11 , using one or more individual circuitries.

FIG. 13 illustrates an example embodiment of an apparatus 1301, whichmay be an apparatus such as, or comprised in, an access node. Theapparatus 1301 may correspond to the access node 104 of FIG. 1 such as(e/g)NodeB or any access node.

The apparatus 1301 may comprise one or more communication controlcircuitry 1320, such as at least one processor, and at least one memory1330, including one or more algorithms 1331, such as a computer programcode (software) wherein the at least one memory and the computer programcode (software) are configured, with the at least one processor, tocause the apparatus to carry out any one of the example functionalitiesof the apparatus described above. Said at least one memory 1330 may alsocomprise at least one database 1332.

Referring to FIG. 13 , the one or more communication control circuitry1320 of the apparatus 1301 comprise at least energy savingfunctionalities circuitry 1321 which is configured to perform collectingdata for training an artificial intelligence or machine learning modelused in controlling the energy saving functionalities according toembodiments. To this end, the energy saving functionalities circuitry1321 of the apparatus 1301 is configured to carry out at least some ofthe functionalities of the apparatus described above, e.g., by means ofFIGS. 2 to 11 , using one or more individual circuitries.

Referring to FIG. 12 and FIG. 13 , the memory 1230, 1330 may beimplemented using any suitable data storage technology, such assemiconductor-based memory devices, flash memory, magnetic memorydevices and systems, optical memory devices and systems, fixed memory,and removable memory.

Referring to FIG. 12 and FIG. 13 , the apparatus 1201, 1301 may furthercomprise different interfaces 1210, 1310 such as one or morecommunication interfaces (TX/RX) comprising hardware and/or software forrealizing communication connectivity according to one or morecommunication protocols. The one or more communication interfaces 1210,1310 may enable connecting to the Internet and/or to a core network of awireless communications network. The one or more communication interface1210, 1310 may provide the apparatus with communication capabilities tocommunicate in a cellular communication system and enable communicationto different network nodes or elements. The one or more communicationinterfaces 1210, 1310 may comprise standard well-known components suchas an amplifier, filter, frequency-converter, (de)modulator, andencoder/decoder circuitries, controlled by the corresponding controllingunits, and one or more antennas.

As used in this application, the term ‘circuitry’ may refer to one ormore or all of the following: (a) hardware-only circuit implementations,such as implementations in only analog and/or digital circuitry, and (b)combinations of hardware circuits and software (and/or firmware), suchas (as applicable): (i) a combination of analog and/or digital hardwarecircuit(s) with software/firmware and (ii) any portions of hardwareprocessor(s) with software, including digital signal processor(s),software, and memory(ies) that work together to cause an apparatus, suchas a terminal device or an access node, to perform various functions,and (c) hardware circuit(s) and processor(s), such as amicroprocessor(s) or a portion of a microprocessor(s), that requiressoftware (e.g. firmware) for operation, but the software may not bepresent when it is not needed for operation. This definition of‘circuitry’ applies to all uses of this term in this application,including any claims. As a further example, as used in this application,the term ‘circuitry’ also covers an implementation of merely a hardwarecircuit or processor (or multiple processors) or a portion of a hardwarecircuit or processor and its (or their) accompanying software and/orfirmware. The term ‘circuitry’ also covers, for example and ifapplicable to the particular claim element, a baseband integratedcircuit for an access node or a terminal device or other computing ornetwork device.

In an embodiment, as shown in FIG. 14 , at least some of thefunctionalities of the apparatus of FIG. 13 may be shared between twophysically separate devices, forming one operational entity. Therefore,the apparatus may be seen to depict the operational entity comprisingone or more physically separate devices for executing at least some ofthe described processes. Thus, the apparatus of FIG. 14 , utilizing suchshared architecture, may comprise a remote control unit RCU 1420, suchas a host computer or a server computer, operatively coupled (e.g., viaa wireless or wired network) to a remote distributed unit RDU 1422located in the base station. In an embodiment, at least some of thedescribed processes may be performed by the RCU 1420. In an embodiment,the execution of at least some of the described processes may be sharedamong the RDU 1422 and the RCU 1420.

Similar to FIG. 13 , the apparatus of FIG. 14 may comprise one or morecommunication control circuitry (CNTL) 1320, such as at least oneprocessor, and at least one memory (MEM) 1330, including one or morealgorithms (PROG) 1331, such as a computer program code (software)wherein the at least one memory and the computer program code (software)are configured, with the at least one processor, to cause the apparatusto carry out any one of the exemplified functionalities of the apparatusdescribed above.

In an embodiment, the RCU 1420 may generate a virtual network throughwhich the RCU 1420 communicates with the RDU 1422. In general, virtualnetworking may involve a process of combining hardware and softwarenetwork resources and network functionality into a single,software-based administrative entity, a virtual network. Networkvirtualization may involve platform virtualization, often combined withresource virtualization. Network virtualization may be categorized asexternal virtual networking which combines many networks, or parts ofnetworks, into the server computer or the host computer (e.g. to theRCU). External network virtualization is targeted to optimized networksharing. Another category is internal virtual networking which providesnetwork-like functionality to the software containers on a singlesystem. Virtual networking may also be used for testing the terminaldevice.

In an embodiment, the virtual network may provide flexible distributionof operations between the RDU and the RCU. In practice, any digitalsignal processing task may be performed in either the RDU or the RCU andthe boundary where the responsibility is shifted between the RDU and theRCU may be selected according to implementation.

In an embodiment, at least some of the processes described in connectionwith FIGS. 2 to 11 may be carried out by an apparatus comprisingcorresponding means for carrying out at least some of the describedprocesses. Some example means for carrying out the processes may includeat least one of the following: detector, processor (including dual-coreand multiple-core processors), digital signal processor, controller,receiver, transmitter, encoder, decoder, memory, RAM, ROM, software,firmware, display, user interface, display circuitry, user interfacecircuitry, user interface software, display software, circuit, antenna,antenna circuitry, and circuitry. In an embodiment, the at least oneprocessor, the memory, and the computer program code form processingmeans or comprises one or more computer program code portions forcarrying out one or more operations according to any one of theembodiments of FIGS. 2 to 11 or operations thereof.

According to an embodiment, there is provided an apparatus comprisingmeans for receiving, from an access node, a configuration for neighbourcell measurements; receiving, from the access node, a message comprisinginformation associated with a mode change in a first radio cell to anenergy saving mode; receiving, in relation to the message, datacollection configuration information for carrying out data collectionmeasurements for training an artificial intelligence or machine learningmodel used in controlling the mode change; carrying out the datacollection measurements and transmitting, to the access node, relatedresults, wherein the data collection measurements are carried outaccording to the data collection configuration at least until a handoverprocedure associated with the mode change is started; carrying out theneighbour cell measurements and transmitting, to the access node,related results for the handover procedure; and carrying out, inresponse to receiving a handover command for the handover procedureassociated with the mode change, a handover to a second radio cell.

According to an embodiment, there is provided an apparatus comprisingmeans for determining and transmitting, at least to a plurality ofapparatuses in a first radio cell, a configuration for neighbour cellmeasurements; determining, for a mode change in the first radio cell toan energy saving mode, a data collection configuration for carrying outdata collection measurements for training an artificial intelligence ormachine learning model used in controlling the mode change;transmitting, when the mode change in the first radio cell to the energysaving mode is initiated, to the plurality of apparatuses, a messagecomprising information associated with the mode change and, in relationto the message, data collection configuration information; receivingresults related to the data collection measurements; receiving, from atleast one of the plurality of apparatuses, results related to theneighbour cell measurements for a handover procedure associated with themode change; and transmitting, to the at least one apparatus, a handovercommand to carry out a handover to a second radio cell.

Embodiments as described may also be carried out in the form of acomputer process defined by a computer program or portions thereof.Embodiments of the methods described in connection with FIGS. 2 to 11may be carried out by executing at least one portion of a computerprogram comprising corresponding instructions. The computer program maybe provided as a computer readable medium comprising programinstructions stored thereon or as a non-transitory computer readablemedium comprising program instructions stored thereon. The computerprogram may be in source code form, object code form, or in someintermediate form, and it may be stored in some sort of carrier, whichmay be any entity or device capable of carrying the program. Forexample, the computer program may be stored on a computer programdistribution medium readable by a computer or a processor. The computerprogram medium may be, for example but not limited to, a record medium,computer memory, read-only memory, electrical carrier signal,telecommunications signal, and software distribution package, forexample. The computer program medium may be a non-transitory medium.Coding of software for carrying out the embodiments as shown anddescribed is well within the scope of a person of ordinary skill in theart.

The term “non-transitory”, as used herein, is a limitation of the mediumitself (i.e., tangible, not a signal) as opposed to a limitation on datastorage persistency (e.g., RAM vs. ROM).

Even though the embodiments have been described above with reference toexamples according to the accompanying drawings, it is clear that theembodiments are not restricted thereto but can be modified in severalways within the scope of the appended claims. Therefore, all words andexpressions should be interpreted broadly, and they are intended toillustrate, not to restrict, the embodiment. It will be obvious to aperson skilled in the art that, as technology advances, the inventiveconcept can be implemented in various ways. Further, it is clear to aperson skilled in the art that the described embodiments may, but arenot required to, be combined with other embodiments in various ways.

1. An apparatus comprising: at least one processor, and at least onememory including computer program code, the at least one memory and thecomputer program code being configured to, with the at least oneprocessor, cause the apparatus at least to: receive, from an accessnode, a configuration for neighbour cell measurements; receive, from theaccess node, a message comprising information associated with a modechange in a first radio cell to an energy saving mode; receive, inrelation to the message, data collection configuration information forcarrying out data collection measurements for training an artificialintelligence or machine learning model used in controlling the modechange; carry out the data collection measurements and transmitting, tothe access node, related results, wherein the data collectionmeasurements are carried out according to the data collectionconfiguration at least until a handover procedure associated with themode change is started; carry out the neighbour cell measurements andtransmitting, to the access node, related results for the handoverprocedure, and carry out, in response to receiving a handover commandfor the handover procedure associated with the mode change, a handoverto a second radio cell.
 2. An apparatus according to claim 1, furthercomprising causing the apparatus to: receive a first conditionassociated with the data collection configuration information; checkwhether the first condition is met; carry out, in response to the firstcondition being met, the data collection measurements and transmitting,to the access node, the related results, and ignore, in response to thefirst condition not being met, the data collection configurationinformation.
 3. An apparatus according to claim 1, further comprisingcausing the apparatus to: receive a second condition for starting thehandover procedure associated with the mode change, wherein the secondcondition comprises at least one of: a time period to lapse afterreceiving the data collection configuration information, and a thresholdfor a difference between the best measured neighbor cell and the firstradio cell when the first radio cell is the best cell, and start, inresponse to the second condition being fulfilled, the handover procedureassociated with the mode change.
 4. An apparatus according to claim 1,wherein the carrying out the data collection measurements furthercomprises causing the apparatus to: associate the data collectionmeasurements related results with additional information indicating thatthe results are data collected for training the artificial intelligenceor machine learning model, and transmit, to the access node, the datacollection measurements related results with the additional informationassociated.
 5. An apparatus according to claim 1, further comprisingcausing the apparatus to: continue carrying out the data collectionmeasurements and transmitting the related results after the handover tothe second radio cell has been carried out.
 6. An apparatus according toclaim 1, further comprising causing the apparatus to: continue carryingout the data collection measurements and transmitting the relatedresults after the handover to the second radio cell has been carried,and wherein the continuing is performed in response to an instruction tocontinue being associated with the data collection configurationinformation for carrying out the data collection measurements.
 7. Anapparatus comprising: at least one processor; and at least one memoryincluding computer program code; the at least one memory and thecomputer program code being configured to, with the at least oneprocessor, cause the apparatus at least to: determine and transmitting,at least to a plurality of apparatuses in a first radio cell, aconfiguration for neighbour cell measurements; determine, for a modechange in the first radio cell to an energy saving mode, a datacollection configuration for carrying out data collection measurementsfor training an artificial intelligence or machine learning model usedin controlling the mode change; transmit, when the mode change in thefirst radio cell to the energy saving mode is initiated, to theplurality of apparatuses, a message comprising information associatedwith the mode change and, in relation to the message, data collectionconfiguration information; receive results related to the datacollection measurements; receive, from at least one of the plurality ofapparatuses, results related to the neighbour cell measurements for ahandover procedure associated with the mode change, and transmit, to theat least one apparatus, a handover command to carry out a handover to asecond radio cell.
 8. An apparatus according to claim 7, furthercomprising causing the apparatus to:determine a first conditionassociated with the data collection configuration information forconfiguring a subset of apparatuses with the data collectionconfiguration, and transmit, to the plurality of apparatuses, the firstcondition with the data collection configuration information.
 9. Anapparatus according to claim 7, further comprising causing the apparatusto: determine a first condition associated with the data collectionconfiguration information for configuring a subset of apparatuses withthe data collection configuration; transmit, to the plurality ofapparatuses, the first condition with the data collection configurationinformation, and, and activate the mode change in the first radio cellto an energy saving mode, when handover commands have been transmittedto the subset of apparatuses.
 10. An apparatus according to claim 7,further comprising causing the apparatus to: determine, for the handoverprocedure associated with the mode change, a second condition comprisingat least one of: a time period to lapse after the data collectionconfiguration information transmitted by the apparatus has beenreceived, and/or a threshold for a difference between the best measuredneighbor cell and the first radio cell when the first radio cell is thebest cell, and transmit the second condition to the plurality ofapparatuses.
 11. An apparatus according to claim 7, further comprisingcausing the apparatus to transmit at least to an access node of thesecond radio cell a request to forward to the apparatus results relatedto the data collection measurements, and receive, from the access nodeof the second radio cell, the results related to the data collectionmeasurements.
 12. An apparatus according to claim 7, further comprisingcausing the apparatus to determine at least one of: a number of radiolink failures that occur after the mode change in the first radio cellto the energy saving mode is initiated; a number of connectionre-establishments that occur after the mode change in the first radiocell to the energy saving mode is initiated; a number of handoverpreparation failures that occur after the mode change in the first radiocell to the energy saving mode is initiated; a handover success rateafter the mode change in the first radio cell to the energy saving modeis initiated; and/or a handover failure rate after the mode change inthe first radio cell to the energy saving mode is initiated.
 13. Amethod comprising: receiving, from an access node, a configuration forneighbour cell measurements; receiving, from the access node, a messagecomprising information associated with a mode change in a first radiocell to an energy saving mode; receiving, in relation to the message,data collection configuration information for carrying out datacollection measurements for training an artificial intelligence ormachine learning model used in controlling the mode change; carrying outthe data collection measurements and transmitting, to the access node,related results, wherein the data collection measurements are carriedout according to the data collection configuration at least until ahandover procedure associated with the mode change is started; carryingout the neighbour cell measurements and transmitting, to the accessnode, related results for the handover procedure; and carrying out, inresponse to receiving a handover command for the handover procedureassociated with the mode change, a handover to a second radio cell. 14.A method comprising: determining and transmitting, at least to aplurality of apparatuses in a first radio cell, a configuration forneighbour cell measurements; determining, for a mode change in the firstradio cell to an energy saving mode, a data collection configuration forcarrying out data collection measurements for training an artificialintelligence or machine learning model used in controlling the modechange; transmitting, when the mode change in the first radio cell tothe energy saving mode is initiated, to the plurality of apparatuses, amessage comprising information associated with the mode change and, inrelation to the message, data collection configuration information;receiving results related to the data collection measurements;receiving, from at least one of the plurality of apparatuses, resultsrelated to the neighbour cell measurements for a handover procedureassociated with the mode change; and transmitting, to the at least oneapparatus, a handover command to carry out a handover to a second radiocell.